Subband decompositions efficiently represent a wide range of signals in forms suitable for compression. The encoded representations of these decompositions may be lossless or lossey. The efficiency of compression depends on reordering and transforming the representation of coefficients, which may decrease the number of bits to be compressed and should organize the bits to be compressed in an order that enhances the effect of compression. One subband decomposition that has become favored is a discrete wavelet transform. Work has been done, but much remains to be done on efficiently transforming a subband decomposition to prepare it for compression.
Therefore, there is an opportunity for inventions which prepare subband decompositions for compression, which include both methods and inverse methods of operating on decompositions and data structures well adapted to preparing subband decompositions for compression.